Write-time intelligence for AI-generated code.
Plumbline is an MCP server that makes AI coding agents work against your project's reality — not their priors. It injects project knowledge before the agent writes, runs mutation testing before you commit, and keeps multi-step work from going off the rails.
One install. One server. Eight tools. One spotter hook.
pip install plumbline-ai[all]| Problem | Tool | What happens |
|---|---|---|
| AI doesn't understand your project | plumbline_context |
Injects conventions, pitfalls, and patterns from your git history |
| AI forgets related files | /btw hook |
Before every Write/Edit, tells the agent which files usually change together |
| AI commits untested mutations | plumbline_verify |
Runs mutation testing on staged changes before commit |
| AI gets sloppy on task 5 of 10 | plumbline_advance |
Evidence gates force discipline across every task |
Add to your .mcp.json:
{
"mcpServers": {
"plumbline": {
"command": "plumbline-mcp"
}
}
}Or run plumbline setup for guided configuration including the /btw hook.
plumbline_context— Project intelligence at session start. Conventions, pitfalls, decisions, hot files.plumbline_query— Search project knowledge mid-task.plumbline_co_changes— Files that change together. Read them before you edit.
plumbline_verify— Pre-commit mutation testing on staged changes. Reports surviving mutants as questions: "Your code still passes tests if X is changed to Y. Is that intentional?"plumbline_explain— Understand a finding in detail.
plumbline_init— Start tracking a development plan.plumbline_advance— Move through phase gates with evidence. The gate validates your evidence is real, not bare assertions.plumbline_status— Check where you are.
Plumbline includes a spotter hook that fires before every file write. It doesn't wait for the agent to ask for help — it injects relevant context when the agent is about to edit a file.
/btw — src/auth.py usually changes with:
- tests/test_auth.py
- middleware/session.py
Did you read these before editing?
The agent never asked. The spotter saw what was happening and briefed it.
v0.1.0 ships at INFORM level — the hook injects context but does not block writes. GATE level — pre-write blocking via mutation analysis of the proposed content — ships in v0.2.0.
plumbline doctorShows which engines are installed and healthy.
Plumbline wraps three proven engines under one surface:
- Context — powered by Sentinel (project intelligence from git history)
- Verify — powered by Seraph (mutation testing, static analysis)
- Gate — powered by Morpheus (plan state, phase gates, evidence validation)
Each engine is optional — install what you need:
pip install plumbline-ai[context] # just project intelligence
pip install plumbline-ai[verify] # just code verification
pip install plumbline-ai[gate] # just plan enforcement
pip install plumbline-ai[all] # everythingAI coding agents skip optional quality checks every time. Not sometimes — every time. We measured this across 49 tool invocations, 9 controlled experiments, and 5 production projects.
Advisory feedback (letter grades, suggestions, warnings) has a 0% action rate. Blocking gates have a ~100% action rate.
Plumbline doesn't advise. It enforces — through evidence-gated task advancement, mutation-based commit verification, and write-time context injection.
v0.1.0 (current): 8 MCP tools + /btw INFORM hook. Pre-commit verification. Plan-state gating. Project intelligence injection.
v0.2.0: plumbline_check returns — pre-write blocking via the /btw hook automatically running mutation analysis on proposed file content before the Write/Edit tool call completes.
v0.3.0: Debrief loop — post-session /plumbline:debrief skill that interviews the agent and feeds hook tuning back into the signal-to-noise optimizer.
MIT.
Built by Evolving Intelligence AI.